Under a Phase II Small Business Innovation Research (SBIR) contract funded jointly by NASA JSC and DARPA, Michigan
Aerospace Corporation developed algorithms for processing 3-D range data to extract information about a target spacecraft, such as
position, orientation and spin rates. The 3-D sensing and processing concepts are uniquely capable of addressing a wide array of needs
in civil space, defense and commercial space communities, such as autonomous satellite servicing for extending the life of expensive
space assets, docking with assets to transfer orbits or de-orbit, performing space situational awareness for defense purposes, or
future Moon and Mars vehicle navigation. Michigan Aerospace Corporation's approach offers the singularly attractive characteristics
that it does not require any targeting aids on the asset of interest; it can provide rendezvous at potentially long ranges (kilometers)
in addition to close-range docking and inspection; and its solid-state design (no moving parts), minimal size, mass and power, make
it practical for micro-satellite platforms. Sensor development and packaging were also assessed.
Software Tools and Potential Applications
Software engineers at Michigan Aerospace Corporation are continuously developing and optimizing robust,
state-of-the-art machine learning algorithms targeting the unique three-dimensional range data provided by scannerless Laser
Detection and Ranging (LADAR) sensors. These 3-D sensor algorithms have been incorporated into a wide variety of cross-platform
applications ranging from target satellite pose-determination to instantaneous human gesture recognition. Michigan Aerospace Corporation
has an expert team of software engineers dedicated to building an advanced software toolbox for the extraction, analysis and recognition
of information and patterns from range images by utilizing the powerful machine-learning paradigm provided by ensembles of decision
trees. This image-processing toolbox can be applied to many unsolved problems in the scientific, biomedical, military and civilian
realms. Some of the potential applications:
- Threat assessment and validation (homeland security/military operations)
- Precise surface damage assessment for aircraft and spacecraft or other objects of interest
Structural analysis and fault detection for bridges and similar structures.
Michigan Aerospace Corporation is an industry leader in algorithm development and the analysis and visualization of
3-D sensor data.
Michigan Aerospace Corporation's PointCloudRenderer Software with simulated point cloud and
corresponding range image of the Hubble Space Telescope
PointCloudRenderer displaying data gathered from a LADAR sensor of a in-house 1/24 scale
replica of the Hubble Space Telescope
Michigan Aerospace Corporation's Satellite Pose Determination End-to-End system
This system is designed to predict the pose of the Hubble Space Telescope but can easily be adapted to predict the pose of essentially any well-defined rigid object.
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